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Epälineaarinen autoregressiivinen hajautettu viive (NARDL) -malli×OLS-regressio (Ordinary Least Squares)×Sileän siirtymän autoregressiivinen (STAR) malli×
TieteenalaEkonometriaEkonometriaEkonometria
MenetelmäperheRegression modelRegression modelRegression model
Syntyvuosi201420191994
KehittäjäShin, Yu & Greenwood-NimmoWooldridge (textbook treatment); classical least squaresTeräsvirta (1994); van Dijk, Teräsvirta & Franses (2002)
TyyppiAsymmetric cointegration / error-correction modelLinear regressionNonlinear time-series regime-switching model
AlkuperäislähdeShin, Y., Yu, B. & Greenwood-Nimmo, M. (2014). Modelling Asymmetric Cointegration and Dynamic Multipliers in a Nonlinear ARDL Framework. In: Sickles, R. & Horrace, W. (Eds.), Festschrift in Honor of Peter Schmidt. Springer. DOI ↗Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860Teräsvirta, T. (1994). Specification, Estimation, and Evaluation of Smooth Transition Autoregressive Models. Journal of the American Statistical Association, 89(425), 208–218. DOI ↗
Rinnakkaisnimetnonlinear ARDL, asymmetric ARDL, Doğrusal Olmayan ARDL (NARDL)ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonusmooth transition autoregressive model, LSTAR, ESTAR, logistic STAR
Liittyvät454
TiivistelmäThe NARDL model, introduced by Shin, Yu and Greenwood-Nimmo in 2014, extends the ARDL framework to capture asymmetric long-run and short-run relationships, testing whether positive and negative changes in a regressor affect the dependent variable differently.Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE).The Smooth Transition Autoregressive (STAR) model is a nonlinear time-series model, developed in Teräsvirta's 1994 framework, that lets the dynamics move smoothly rather than abruptly between two regimes. The logistic variant (LSTAR) captures asymmetric business cycles and the exponential variant (ESTAR) captures purchasing-power-parity deviations.
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ScholarGateVertaile menetelmiä: NARDL Model · OLS Regression · STAR Model. Haettu 2026-06-18 osoitteesta https://scholargate.app/fi/compare